Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/70823
DC FieldValueLanguage
dc.contributor.authorMartínez López, Albaen_US
dc.contributor.authorTrujillo Castellano, Lourdesen_US
dc.contributor.authorChica González, Manuelen_US
dc.date.accessioned2020-03-11T07:54:46Z-
dc.date.available2020-03-11T07:54:46Z-
dc.date.issued2020en_US
dc.identifier.isbn978-3-030-37751-9en_US
dc.identifier.issn1871-3033-
dc.identifier.urihttp://hdl.handle.net/10553/70823-
dc.description.abstractWith the opening of the Panama Canal, Chile is adapting its transport logistics to the expected arrival of larger container vessels by assuming the establishment of a hub port in its central region. This paper tackles the feasibility of the intermodal chains through MoS to feed the North and the South regions from this central hub port. Due to the features of Chile, the intermodal distances are similar to the unimodal distances. This fact along with the remarkable imbalance of the cargo flows between the North and the South are an additional challenge for the success of the intermodality. In order to support the opportunities of success of the intermodality this study defines, through the optimization of a mathematical model, the most adequate fleets for MoS in the North and South of Chile. Likewise, assuming identical conditions for all Chilean ports (previous scenarios), the resolution of the model identifies the most suitable peripheral ports to articulate MoS from a large-scale hub port in the central region of Chile. The results show that, the intermodality is a competitive solution in the north, but it is not in the south when optimized fleets are used.en_US
dc.languageengen_US
dc.publisherSpringeren_US
dc.sourceComputation and Big Data for Transport. Digital Innovations in Surface and Air Transport Systems/ Pedro Diez; Pekka Neittaanmäki; Jacques Periaux; Tero Tuovinen; Jordi Pons-Prats (eds), Computation and Big Data for Transport. Computational Methods in Applied Sciences, vol 54, p. 181-193en_US
dc.subject531212 Transportes y comunicacionesen_US
dc.subject.otherShort sea shippingen_US
dc.subject.otherMotorways of the seaen_US
dc.subject.otherIntermodal chainsen_US
dc.subject.otherMulti-objective optimizationen_US
dc.subject.otherEvolutionary algorithmsen_US
dc.titleEstablishment of MoS in Chile: Pertinence Assessment Through an Analysis of Previous Scenariosen_US
dc.typeinfo:eu-repo/semantics/bookParten_US
dc.typeBookParten_US
dc.relation.conferenceComputation and Big Data in Transport (CM3 2017)en_US
dc.identifier.doi10.1007/978-3-030-37752-6_11en_US
dc.description.lastpage193en_US
dc.description.firstpage181en_US
dc.relation.volume54en_US
dc.investigacionCiencias Sociales y Jurídicasen_US
dc.type2Capítulo de libroen_US
dc.identifier.eisbn978-3-030-37752-6-
dc.utils.revisionen_US
dc.identifier.supplement1871-3033-
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-ECOen_US
dc.description.spiqQ1
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.event.eventsstartdate22-11-2017-
crisitem.event.eventsenddate23-11-2017-
crisitem.author.deptGIR Economía de las Infraestructuras, el Transporte y el Turismo-
crisitem.author.deptDepartamento de Ingeniería Mecánica-
crisitem.author.deptGIR Economía, Comercio y Transporte Marítimo-
crisitem.author.deptDepartamento de Análisis Económico Aplicado-
crisitem.author.deptGIR Economía de las Infraestructuras, el Transporte y el Turismo-
crisitem.author.deptDepartamento de Ingeniería Mecánica-
crisitem.author.orcid0000-0003-4464-0600-
crisitem.author.orcid0000-0002-0918-5625-
crisitem.author.orcid0000-0002-3580-0935-
crisitem.author.parentorgDepartamento de Análisis Económico Aplicado-
crisitem.author.parentorgDepartamento de Análisis Económico Aplicado-
crisitem.author.parentorgDepartamento de Análisis Económico Aplicado-
crisitem.author.fullNameMartínez López, Alba-
crisitem.author.fullNameTrujillo Castellano, Lourdes-
crisitem.author.fullNameChica González, Manuel José-
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